In practical FLchain systems, when a mobile user serves as both training nodes and miners, how to encourage users to join the FLchain process is a key challenge. blackA user may not be willing to devote its resources to perform mining if it does not have much economic benefits blackto compensate the consumption of computational and storage resources [1]}, [2]}. This issue is particularly important in server-less scenarios where there is no any servers (e.g., MEC servers) to coordinate the FLchain process and manage the blockchain mining. Moreover, the heterogeneity among FLchain nodes caused by the different characteristics (e.g., CPU and memory) of devices can also result in imbalance among nodes [3]}. Therefore, the clients with better computational capability can dominate the training and mining to obtain more rewards. How to achieve an economic fairness among nodes in FLchain thus is a challenging issue.
